Key Points: Will Claude Code Be the Final Winner?

Hello, I am Wang Yuquan, and this is Wang Yuquan’s News Commentary.

The AI Landscape

In recent months, the AI field has been bustling with activity. Projects like OpenClaw, NanoClaw, and Hermes, along with many others you may not have heard of yet, are emerging continuously.

These projects boast their own strengths and innovations, such as enhanced memory capabilities, reflective abilities, multi-agent collaboration for complex tasks, and even workflows that simulate the execution processes of small organizations.

On the surface, it seems like a vibrant era of innovation.

However, a somewhat unusual phenomenon is emerging: once these innovations are proven effective, they are quickly absorbed into a single company’s product—Claude Code.

Thus, we believe that for most individuals and businesses, rather than chasing every trend, it is more beneficial to focus on Claude Code, which seems to possess a unique ability to platformize and productize validated practices from the open-source community.

The Absorption Mechanism

This trend was clearly reflected at Anthropic’s recent Code with Claude developer conference. Anthropic introduced a mechanism called Dreaming, signaling that Claude Code is systematically absorbing effective mechanisms from the entire agent field.

Specifically, Dreaming reviews historical behavior records of agents across multiple sessions, organizes, deduplicates, and abstracts stable patterns, then writes them back into the system’s memory layer. For example, recurring operational patterns are merged into stable processes, obsolete experiences are automatically cleared, and behavioral patterns that appear across tasks are abstracted into default references for future tasks.

To put it simply, it’s akin to a person who not only experiences various events during the day but also reorganizes those experiences during sleep or rest, forming more stable judgment habits and behaviors.

Dreaming enables agents not only to remember more but also to organize their experiences and self-optimize, granting them a capacity for continuous evolution, rather than starting from scratch each time.

However, have you noticed? This ability for “experience accumulation” and “long-term behavior optimization” is somewhat similar to the recently popular Hermes Agent, or it may have been inspired by it.

Looking back at Anthropic’s Claude Code, you will find that it has consistently drawn from various strengths. For instance, the long-term memory mechanism, which allows agents to retain information across sessions and utilize it in new tasks, has been a challenge addressed by OpenClaw and earlier memory agent frameworks, not an original invention of Claude Code.

Claude Code later integrated this memory mechanism, but instead of simply connecting an external memory module, it decomposed memory into a three-layer structure, embedding it into different stages of system operation. Some memories are loaded at the start of a task, some are dynamically generated during execution, and others are consolidated after task completion, influencing subsequent tasks.

Similarly, the “task decomposition and multi-agent collaboration mechanism” stems from explorations by NanoClaw and various multi-agent frameworks. Claude Code adopted this idea but made task decomposition a default behavior of the model.

The recently discussed harness essentially refers to workflow orchestration. After absorbing this capability, Claude Code no longer treats workflows as external designs; it dynamically generates execution paths based on task objectives and continuously adjusts the structure during execution.

Through the continuous absorption and optimization of these singular innovations, Claude Code evolves from a programming tool into the most popular agent, becoming Anthropic’s flagship product.

Patterns in Innovation

What we want to emphasize is that this is precisely the typical pattern in technological waves. Initially, there are dispersed innovations, with various teams attempting to solve specific localized problems.

Then comes ecological prosperity, where different singular innovations begin to combine and reconstruct, forming numerous frameworks and products.

However, the next phase is absorption. Leading companies in a platform or field leverage their unique advantages to occupy critical nodes in the ecosystem, transforming validated practices into internal capabilities.

This process has occurred many times in the past. In the PC era, the early software ecosystem was highly fragmented, with each tool addressing a small issue, such as file management, office processing, and browsing. Eventually, Windows and Office gradually integrated these capabilities.

In the mobile internet era, numerous independent apps initially solved single problems, such as payment, instant messaging, short videos, news reading, and social networking. Over time, these capabilities were absorbed by a super app, becoming internal functional modules.

In summary, it starts with widespread dispersed innovation, but ultimately, these innovations converge into a few platform-level companies and systems.

Currently, this process is happening again in the agent field. In the wave of agents, technological innovations will continue to occur, and the speed of absorption will also accelerate.

Therefore, the key question is no longer “who made a particular functional innovation”; we should focus on “who can continuously absorb and reconstruct different agent capabilities,” meaning where the successfully validated innovations will ultimately flow.

At present, Claude Code appears to be the answer. Although it is also an agent, it possesses the broadest developer and agent user base due to the advanced foundation model Claude, occupying a unique position in the agent field, becoming the ultimate system capable of absorbing innovations across all industries.

So, perhaps the century-old dilemma that will challenge all entrepreneurs is returning: What will you do if Anthropic decides to pursue what you are doing?

It is evident that future competition in the agent space will not only depend on what new features you possess but also on whether you have core competencies that others cannot replicate or replace.

Does this spark any insights for you? Feel free to share your thoughts in the comments section.

Conclusion

That’s all for today’s content! Wang Yuquan’s News Commentary, see you tomorrow.